编写一个简单的Java程序，实现从HDFS中读取文件并计算文件中单词的数量。

好的，以下是一个简单的Java程序，实现从HDFS中读取文件并计算文件中单词的数量：

import java.io.IOException;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class WordCount {

    public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable>{

        private final static IntWritable one = new IntWritable(1);
        private Text word = new Text();

        public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
            StringTokenizer itr = new StringTokenizer(value.toString());
            while (itr.hasMoreTokens()) {
                word.set(itr.nextToken());
                context.write(word, one);
            }
        }
    }

    public static class IntSumReducer extends Reducer<Text,IntWritable,Text,IntWritable> {
        private IntWritable result = new IntWritable();

        public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
            int sum = 0;
            for (IntWritable val : values) {
                sum += val.get();
            }
            result.set(sum);
            context.write(key, result);
        }
    }

    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        FileSystem fs = FileSystem.get(conf);

        if (args.length < 2) {
            System.err.println("Usage: WordCount <input path> <output path>");
            System.exit(-1);
        }

        Job job = Job.getInstance(conf, "word count");
        job.setJarByClass(WordCount.class);
        job.setMapperClass(TokenizerMapper.class);
        job.setCombinerClass(IntSumReducer.class);
        job.setReducerClass(IntSumReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        // 设置输入路径和输出路径
        FileInputFormat.addInputPath(job, new Path(args[0]));
        Path outputPath = new Path(args[1]);
        if (fs.exists(outputPath)) {
            fs.delete(outputPath, true);
        }
        FileOutputFormat.setOutputPath(job, outputPath);

        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}

在执行时，需要指定输入路径和输出路径，例如：

hadoop jar wordcount.jar WordCount /input/sample.txt /output

其中，/input/sample.txt表示输入文件的路径，/output表示输出路径。